Several methods have been put forward to extract network backbones. For static weighted networks, the simplest way of filtering edges is to remove all the edges with weight below a given threshold value. More principled procedures use statistical tests based on null models to compare the weights of the edges with the ones that would be generated at random by a certain null model [1]}, [2]}, [3]}, [4]}, [5]}. One then fixes a desired significance level and selects only those edges whose weight cannot be explained by the null model at the chosen significance level. These significant edges form the backbone of the network.
